what is big data?
big data is a field that deals with data sets that are too large to be handled by traditional data processing application software.
Today we show you 10 of the best big data books that will cover:
You are reading: Best big data books
- big data fundamentals
- big data analytics
- Ethics
and much more.
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tldr: best big data books🔥 best overall 🔥big data: concepts, technology and architecture💥 best for beginners 💥big data fundamentals: concepts, drivers & techniques💸 best value 💸big data processing with apache spark
learn big data
1. big data: concepts, technology and architecture
🚨 Ideal For: Data Scientists, Data Engineers, Database Administrators, Business Intelligence Analysts💥 Major Topics: Data Analytics, Data Mining , machine learning
big data: concepts, technology and architecture by balamarugan balusamy, nandhini abirami r, seifedine kadry and amir gandomi is aimed at data scientists, data engineers and database administrators.
You will learn each step of the big data life cycle. this includes:
- structured, unstructured & semi-structured data
- data warehousing solutions
- data mining and analytics
and much, much more.
Do you want to take a course on big data? see the introduction to big data and hadoop on the interactive platform educative.io.
then you will learn big data technologies like apache hadoop and apache flume.
This book is one of the best modern big data books we could find.
2. big data management: data governance principles for big data analytics
🚨 Ideal for: data scientists, data engineers, and corporate leaders💥 major topics: data security, privacy, lifecycle management
managing big data by peter ghavami is one of the best big data books focused on data analysis.
big data management is ideal for data scientists, data engineers, and corporate leaders.
Here you’ll examine policies, strategies, and recipes for managing your big data. covers:
- data security
- privacy
- lifecycle management
and more.
3. big data analysis with r
🚨 Ideal For: Data Scientists💥 Major Topics: Cloud-based data solutions, relational and non-relational databases, machine learning
In Simon Walkowiak’s Analyzing Big Data with R (package), you’ll learn the big data industry standards. then you will get an introduction to r programming.
In addition, you will learn about cloud-based big data solutions such as Amazon EC2 and Microsoft Azure.
You will also learn about other big data tools, such as Apache Hadoop and Apache Spark’s machine learning library, Spark mllib.
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… I don’t think there is a better resource for learning r for data analysis…”
4. Spark: The Ultimate Guide: Big Data Processing Made Easy
🚨 ideal for: spark enthusiasts who want to dig deeper into the framework💥 major topics: apis, spark clusters, machine learning
Spark: The Definitive Guide makes our list of the best big data books because it was written by Bill Chambers and Matei Zaharia – the creators of Apache Spark.
here you will learn how to use, implement and maintain spark, with an emphasis on spark 2.0.
💡 spark was created at uc berkley’s amplab in 2009. in 2013 it was donated to the apache software foundation where it became apache 2.0.
will start with an overview of big data and spark. then you will learn about some of the main spark api like:
- dataframes
- sql
- datasets
Finally, you’ll discover mllib for machine learning classification and recommendation.
5. big data analytics with sas
🚨 ideal for: sas professionals, data analysts💥 main topics: predictive modeling, forecasting, optimization, reporting
sas is a statistical software package used for data management, analysis, and more. David Pope’s big data analytics with sas (package) was written to help you harness the powers of sas to analyze and process big data.
With real-world and practical examples, you’ll discover:
- predictive modeling
- forecasting
- optimization
- reporting
big data analytics with sas will teach you how to prepare data for analysis, perform predictive forecasting, and more.
6. data science and big data analytics
🚨 ideal for: data scientists💥 main topics: techniques, implementation, tools
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data science and big data analytics is designed to help you harness the power of data to gain new insights.
ready to dive into pyspark? Check out the fundamentals of big data with pyspark course on datacamp.
you will discover:
- concepts
- principles
- applications
data science and big data analytics will also help you become a contributing member of your data science team.
one of the best books for beginners on big data analytics.
7. Big Data Fundamentals: Concepts, Drivers & techniques
🚨 ideal for: data scientists, business managers💥 main topics: business motivations, big data integration
big data fundamentals: concepts, drivers & techniques by thomas erl, wajid khattak, and paul buhler is possibly one of the best big data books for data scientists and business managers.
You will learn about the 5 vs. datasets in big data:
- volume
- variety
- speed
- truth
- value
💡 depending on who you ask, there are 3 to 7 versus big data. but three are always the same: volume, variety and speed.
big data fundamentals is packed with case studies and diagrams.
8. big data processing with apache spark
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🚨 ideal for: software engineers, architects, IT professionals💥 main topics: common spark operations, spark integration with aws
Big Data Processing with Apache Spark (Packt) by Manuel Galeano is one of the best big data books for software engineers and IT professionals.
First, you’ll start by learning the fundamentals of spark, such as dataframes, sql, and datasets. You’ll also explore the basic concepts behind spark, such as:
- spark streaming
- machine learning extensions
- structured streaming
and much more.
As you progress, you’ll discover how to write Python programs that interact with Spark. will also work on integrating spark streaming with aws.
9. big data ethics: balance between risk and innovation
🚨 ideal for: individuals and organizations💥 main topics: ethical data processing, data handling practices
kord davis’s big data ethics is a bit different than the other big data books on our list.
Instead of teaching you the technicalities of big data, you’ll learn how to handle it ethically.
This book has a strong focus on privacy and identity.
You will discover techniques to review your data handling practices and see if they align with the values of the organization.
then you will design plans to close the discrepancies between values and practices.
ultimately, you’ll learn to maintain that balance while overcoming risks and other challenges.
10. big data: a brief introduction
🚨 ideal for: data scientists💥 main topics: the need for big data in today’s world
on big data: a very brief introduction by dawn holmes, you will not work with large data sets.
Instead, you’ll learn how big data is used in business, government, and the healthcare industry.
Want an overview of big data? check out the big data: the big picture course at pluralsight.
There are a variety of case studies that examine what the data looks like:
- stored
- analyzed
- exploited
This includes examining data security and smart home devices.
big data books: conclusion
Today we look at 10 big data books:
🔥 best overall 🔥big data: concepts, technology and architecture
💥 best for newbies 💥big data fundamentals: concepts, drivers & techniques
💸 best value 💸big data processing with apache spark
So, whether you want a decent Apache Spark book, a good value, or just getting started with big data, we believe there are big data books for just about everyone.
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